Home / Models / SmolLM2 1.7B Instruct / NVIDIA RTX 2060 SUPER 8 GB

Calculated memory fit · not a benchmark

Can SmolLM2 1.7B Instruct run on NVIDIA RTX 2060 SUPER 8 GB?

Yes. Calculated memory fit: SmolLM2 1.7B Instruct can run entirely in this GPU’s usable VRAM at one or more supported quantizations.

Can it run?

Can it run?
Yes, full GPU fit (calculated estimate).
Full GPU fit?
Yes
Model
SmolLM2 1.7B Instruct · 1.7B
GPU
NVIDIA RTX 2060 SUPER 8 GB · 8 GB advertised

Memory calculation

Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.

Model weights1.0 GB
KV cache1.5 GB
Runtime reserve0.6 GB
Safety margin0.3 GB
Required (estimated)3.3 GB
GPU usable VRAM7.2 GB

Result: FITS IN VRAM

Quantization table

Quantization2K4K8K
BF16FitsFitsFits
FP16FitsFitsFits
Q3FitsFitsFits
Q4FitsFitsFits
Q5FitsFitsFits
Q6FitsFitsFits
Q8FitsFitsFits

What fits entirely in VRAM?

What requires RAM offload?

Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.

Available graphics cards

These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.

Check price on Amazon

MSI

MSI GAMING GeForce RTX 2060 SUPER X

8 GB · Amazon unmatched

Check availability
MSI

MSI ARMOR GeForce RTX 2060 SUPER OC

8 GB · Amazon unmatched

Check availability
GIGABYTE

GIGABYTE AORUS GeForce RTX 2060 SUPER 8G

8 GB · Amazon unmatched

Check availability

Sources

Model: official config HuggingFaceTB/SmolLM2-1.7B-Instruct (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: FITS_IN_VRAM. Amazon: affiliate commerce match, not a spec source.